Computer vision for yarn microtension measurement

Yarn tension is an important parameter for assuring textile quality. In this paper, an optical method to measure microtension of moving yarn automatically in the winding system is proposed. The proposed method can measure microtension of the moving yarn by analyzing the captured images. With a line laser illuminating the moving yarn, a linear array CCD camera is used to capture the images. Design principles of yarn microtension measuring equipment based on computer vision are presented. A local border difference algorithm is used to search the upper border of the moving yarn as the characteristic line, and Fourier descriptors are used to filter the high-frequency noises caused by unevenness of the yarn diameter. Based on the average value of the characteristic line, the captured images were classified into sagging images and vibration images. The average value is considered a sag coordinate of the sagging images. The peak and trough coordinates of the vibration are obtained by change-point detection. Then, according to axially moving string and catenary theory, we obtain the microtension of the moving yarn. Experiments were performed and compared with a resistance strain sensor, and the results prove that the proposed method is effective and of high accuracy.